TF_Status* status);

// Fills in `dims` with the list of shapes in the attribute `attr_name` of
// `oper` and `num_dims` with the corresponding number of dimensions. On return,
// for every i where `num_dims[i]` > 0, `dims[i]` will be an array of
// `num_dims[i]` elements. A value of -1 for `num_dims[i]` indicates that the

                         DataType value, ForwardOperation*);
absl::Status SetAttrShape(AbstractOperation*, const char* attr_name,
                          const int64_t* dims, const int num_dims,
                          ForwardOperation*);
absl::Status SetAttrFunction(AbstractOperation*, const char* attr_name,
                             const AbstractOperation* value, ForwardOperation*);

TF_Tensor* Int8Tensor(const int64_t* dims, int num_dims, const char* values) {
  int64_t num_values = 1;
  for (int i = 0; i < num_dims; ++i) {
    num_values *= dims[i];
  }
  TF_Tensor* t =
      TF_AllocateTensor(TF_INT8, dims, num_dims, sizeof(char) * num_values);
  memcpy(TF_TensorData(t), values, sizeof(char) * num_values);
  return t;
}

TF_Tensor* Int32Tensor(const int64_t* dims, int num_dims,

    return nullptr;
  }

  size_t total_bytes = dl_tensor->dtype.bits / 8;
  for (int i = 0; i < num_dims; i++) {
    total_bytes *= dims[i];
  }

  if (dl_tensor->strides != nullptr &&
      !IsValidStrideCompactRowMajorData(dl_tensor->shape, dl_tensor->strides,
                                        num_dims)) {
    status->status = tensorflow::errors::InvalidArgument(
        "Invalid strides array from DLPack");

TEST(CAPI, TestTensorNonScalarBytesAllocateDelete) {
  const int batch_size = 4;
  const int num_dims = 2;
  int64_t* dims = new int64_t[num_dims];
  int64_t num_elements = 1;
  dims[0] = batch_size;
  dims[1] = 1;
  for (int64_t i = 0; i < num_dims; ++i) {
    num_elements *= dims[i];
  }
  TF_Tensor* t = TF_AllocateTensor(TF_STRING, dims, num_dims,
                                   sizeof(TF_TString) * num_elements);

tensorflow::shape_inference::ShapeHandle ShapeHandleFromDims(
    tensorflow::shape_inference::InferenceContext* ic, int num_dims,
    const int64_t* dims) {
  if (num_dims != -1) {
    std::vector<tensorflow::shape_inference::DimensionHandle> dim_vec;
    dim_vec.reserve(num_dims);
    for (int i = 0; i < num_dims; ++i) {
      dim_vec.push_back(ic->MakeDim(dims[i]));
    }
    return ic->MakeShape(dim_vec);
  } else {

  virtual absl::Status SetAttrType(const char* attr_name, DataType value) = 0;
  virtual absl::Status SetAttrShape(const char* attr_name, const int64_t* dims,
                                    const int num_dims) = 0;
  virtual absl::Status SetAttrShape(const char* attr_name,
                                    const PartialTensorShape shape);
  virtual absl::Status SetAttrFunction(const char* attr_name,

// Read the shape of a variable and write to `dims`
TF_CAPI_EXPORT extern void TF_CheckpointReaderGetVariableShape(
    TF_CheckpointReader* reader, const char* name, int64_t* dims, int num_dims,
    TF_Status* status);
// Get the number of dimension of a variable
TF_CAPI_EXPORT extern int TF_CheckpointReaderGetVariableNumDims(
    TF_CheckpointReader* reader, const char* name);
// Load the weight of a variable

// is needed a static_cast can be applied.
class ImmediateExecutionTensorHandle : public AbstractTensorHandle {
 public:
  // Returns number of dimensions.
  virtual absl::Status NumDims(int* num_dims) const = 0;
  // Returns number of elements across all dimensions.
  virtual absl::Status NumElements(int64_t* num_elements) const = 0;
  // Returns size of specified dimension
  //

// If the number of dimensions is unknown, `num_dims` must be set to
// -1 and `dims` can be null.  If a dimension is unknown, the
// corresponding entry in the `dims` array must be -1.
TF_CAPI_EXPORT extern void TFE_OpSetAttrShape(TFE_Op* op, const char* attr_name,
                                              const int64_t* dims,
                                              const int num_dims,